當光源過亮或是過暗時，在暗部或亮部的細節可能無法在顯示器上完整呈現；且有些自然場景的動態範圍超過人眼所能感受的範圍。因此，攝影設備及人眼知覺之間的差異將成為完整呈現影像場景的瓶頸。影像強化是一個可以改善影像品質及人眼視覺感受的方法。此外，影像強化可應用在許多領域，例如：遙測、醫學影像分析、圖形辨識、高解析度電視、顯微造影技術等。
此篇論文提出一個基於分區曝光系統對比強化適應演算法，用來改善影像的視覺品質，及呈現隱藏的細節及增加影像對比，尤其是當拍攝場景極缺乏亮度或是亮度不均時，例如：夜間攝影、背光場景等。本演算法由兩個步驟所構成，適應性全域亮度強化法及適應性區域對比強化法。適應性全域亮度強化法是一個基於分區曝光顯影系統資訊的全域亮度轉換函數，此步驟不但在過暗區域提升亮度且在過亮區域降低亮度。適應性區域對比強化法藉由區域亮度的不連續性調整相鄰像素之間的亮度，進而改善區域的對比度，且清楚呈現影像細節。
實驗結果顯示，我們所提出的演算法在加強對比度、保留細節特性及銳化物件邊緣方面都有不錯的效果。且經我們的演算法處理後的影像，其細節紋理可容易被觀察到。並基於主觀及客觀的評估方法，可證明我們提出的演算法在影像強化方面十分有效。且經由這些效能評估方法，可知道我們的方法相較於其他方法，例如：結合相鄰像素的非線性強化演算法(AINDANE)、針對彩色影像的基於區域方法之非線性轉換函數強化演算法(NTFBLA)、結合銳度補償的可調式銳利度強化演算法(ALTHE)及基於權重並結合分群之直方圖等化的對比強化演算法(WBCHE)，我們所提出的方法可產生較佳的影像。

If the lighting condition is over bright or over dark, the details in the brightest region or shadow region are usually hidden on the display device. And some of the natural images that exceed dynamic range of human eyes perceive. Thus, a serious difference between capturing device and human perception lead to the bottleneck in representing an image completely. The image enhancement is a method to improve the image quality to approach human perception. Besides, image enhancement could apply to many fields, such as remote sensing, medical image analysis, pattern recognition, high definition television, microscopic imaging, and so on.
This thesis presents an adaptive contrast enhancement algorithm based on Zone System to improve the visual quality of digital images that are captured under extremely low or non-uniform lighting conditions, for example photographing at night, or carrying the situation facing backward the light. And the proposed algorithm could reveal hidden image details or increase the contrast of an image with low dynamic range. The proposed algorithm is comprised two processes: adaptive global luminance enhancement and adaptive neighborhood-dependent contrast enhancement. The adaptive global luminance enhancement algorithm is a global intensity transform function based on Zone System information. This process not only upgrades the luminance of darker regions but also degrades the luminance of brighter regions. The adaptive neighborhood-dependent contrast enhancement adjusts the intensity of each pixel based on the discontinuities of the local luminance. It also improves the contrast of local region and reveals the details of image clearly.
Experimental results show that the proposed algorithm has good performance on enhancing contrast, preserving more detail of characteristics and sharpening edges of objects. We could observe textures and details easily after applying the proposed algorithm. Based on subjective and objective evaluations, the proposed algorithm proves the efficient performance in image enhancement. Those criteria of evaluations show that the proposed algorithm produces better enhanced images in comparison with other algorithms like AINDANE, NTFBLA, ALTHE and WBCHE.

[1] “A simplified Zone system for making good exposures”, (2012), [Online], Available: http://www.normankoren.com/zonesystem.htm
[2] “Understanding & Using Ansel1 Adam’s Zone System”, (2012), [Online], Available: http://photo.tutsplus.com/articles/theory/understanding-using-ansel-adams-zone-system/
[3] “Why You NEED the Zone System for Digital…”, (2012), [Online], Available : http://f164.com/the-zone-system-for-digital/10/2011/
[4]“A Photo Teacher”, (2012), [Online], Available:http://aphototeacher.com/2007/08/29/the-zone-system-and-the-refined-photographic-print/
[5]“Fundamentals of Film Exposure”, (2012), [Online], Available: http://micro.magnet.fsu.edu/primer/photomicrography/filmexposure.html
[6]“Organizing Color”, (2012), [Online], Available: http://viz.aset.psu.edu/gho/sem_notes/color_2d/html/primary_systems.html
[7]“The HSV Colorspace”, (2012), [Online], Available: http://www.dig.cs.gc.cuny.edu/manuals/Gimp2/Grokking-the-GIMP-v1.0/node51.html
[8]“Physics Frums”, (2012), [Online], Available: http://www.physicsforums.com/showthread.php?t=360725
[9]“File:Low-key cat.jpg”, (2012), [Online], Available: http://en.wikipedia.org/wiki/File:Low-key_cat.jpg
[10] “Underexposure in UFRaw/GIMP?”, (2012), [Online], Available: http://www.pentaxforums.com/forums/digital-processing-software-printing/91496-underexposure-ufraw-gimp.html
[11] “Dynamic Range Increase - DRI Pro v1.1”, (2012), [Online], Available:http://www.fredmiranda.com/DRI/
[12] ”Kodak Lossless True Color Image Suite”, (2012), [Online], Available:http://r0k.us/graphics/kodak/
[13]”High Key Blast”, (2012),[Online],Available:http://www.autofx.com/products/mttc/effects/highkeyblast.html
[14] “Gaussian filter, or Gaussian blur”, (2012),[Online],Available:http://www.librow.com/articles/article-9
[15] “Zone system”, (2012), [Online], Available: http://hsuotto.blogspot.tw/2007/04/zone-system.html
[16] Ansel Adams, “The Negative- Ansel Adams Photography Series 2”, Little Brown and Company, New York Boston, Page(s): 47-98, 2002.
[17] Ansel Adams, ”The Camera”, Little Brown and Company, New York Boston,1995
[18] Martin Cad´ and Pavel Slav´ık, "The Naturalness of Reproduced High Dynamic Range Images", Ninth International Conference on Information Visualisation, Page(s): 920-925, July 2005.
[19] M. Cadik, M. Wimmer, L. Neumann and A. Artusi, “Image Attributes and Quality for Evaluation of Tone Mapping Operators”, Proceedings of Pacific Graphics 2006, 14th Pacific Conference on Computer Graphics and Applications, Page(s): 35-44. October 2006.
[20] S. D. Chen and A. R. Ramli, “Minimum mean brightness error bi-histogram equalization in contrast enhancement”, IEEE Trans. Consumer Electron., vol. 49, no. 4, Page(s): 1310–1319, Nov. 2003.
[21] G. Deng, L. W. Cahill, and G. R. Tobin, “The study of logarithmic image processing model and its application to image enhancement”, IEEE trans. Process. Vol. 4, Page(s): 506-512, 1995
[22] Huan Dai, Xiaofeng Gu, Lei He and Zhouye Chen, “An adaptive color image enhancement algorithm based on local luminance discontinuity”, 2010 3rd International Congress on Image and Signal Processing (CISP), 2010, Vol.2, Page(s):626-630
[23] Ahmet M. Eskicioglu and Paul S. Fisher, “Image Quality Measures and Their Performance”, IEEE Transactions on Communications, Vol. 43, No. 12, December 1995.
[24] R. C. Gonzalez and R. E. Woods, “Digital Image Processing”, Upper Saddle River, NJ: Prentice-Hall, 2006
[25] Deepak Ghimire and Joonwhoan Lee, “Nonlinear Transfer Function-Based Local Approach for Color Image Enhancement”, IEEE Transactions on Consumer Electronics, 2011, Vol. 57, Page(s):858-865
[26] R. C. Gonzalez and R. E. Woods, ”Digital Image Processing (3rd Edition). “, Prentice-Hall, Inc., Upper Saddle River, NJ, USA, 2006, Sect. 2. 1.
[27] Hasselblad, ”The Hasselblad Zone System”, Little Brown and Company, New York Boston, 1999
[28] Linan Jiao, Zhaoyun Sun and Aimin Sha, "Improvement of Image Contrast with Local Adaptation," mmit, vol. 2, Page(s):51-54, 2010 Second International Conference on Multi Media and Information Technology, 2010
[29] Chris Johnson, “The Practical Zone System: For Film and Digital Photography”, 4th edition, Focal Press, 2006
[30] D. J. Jobson, Z. Rahman, and G. A. Woodell, “Statistic of visual representation” ,Proc. SPIE 4736, Page(s): 25-35, 2002.
[31] Y. T. Kim, “Contrast enhancement using brightness preserving bi-histogram equalization”, IEEE Trans. Consumer Electron., vol. 43, no. 1, Page(s): 1–8, Feb. 1997.
[32] J.Y. Kim, L.S. Kim and S.H. Hwang, "An advanced contrast enhancement using partially overlapped sub-block histogram equalization," IEEE Trans. on Circuits and Systems for Video Technology, Vol. 11, Issue 4, Page(s):475-484, Apr. 2001. [33]
[33] T.K. Kim, J.K. Paik and B.S. Kang, "Contrast enhancement system using spatially adaptive histogram equalization with temporal filtering," IEEE Trans. on Consumer Electronics, Vol.44, Issue 1, Page(s): 82-87, Feb. 1998.
[34] J. Y. Kim, L.-S.Kim, and S.-H. Hwang, “An advanced contrast enhancement using partially overlapped sub-block histogram equalization,”IEEE Trans. Circuits Syst. Video Technol”, vol. 11, no. 4, Page(s): 475–484, Apr. 2001.
[35] M. Hanmandlu, O. P. Verma, N.K. Kumar and M. Kulkarni,” A Novel Optimal Fuzzy System for Color Image Enhancement Using Bacterial Foraging”, IEEE Transactions on Instrumentation and Measurement, 2009, Vol. 58, Issue. 8, Page(s): 2867-2879
[36] E. Nezhadarya, M. B. Shamsollahi, “Image Contrast Enhancement by Contourlet Transform”, 48th International Symposium Elmar, 2006, Page(s): 81-84.
[37] S. K. Naik and C. A. Murthy, “Hue-preserving color image enhancement without gamut problem,” IEEE Trans. Image Process., vol. 12, no. 12, Page(s): 1591–1598, Dec. 2003.
[38] Z. Qinwu, B. Zhengzhong, Z. Ddlong, “Denoising and Contrast Enhancement off Ultrasound Speckle Image Based on Wavelet”, Signal Processing, IEEE 6thInternational Conference, 2002, Page(s):1500-1503.
[39] G. Ramponi, N. K. Strobel, S. K. Mitra, and T.-H. Yu, “Nonlinear unsharp masking methods for image contrast enhancement” Journal of electronic imaging, vol. 5, no. 3, Page(s): 353-366, July 1996.
[40] J. Starck, F. Murtagh, E. J. Candès, and D. L. Donoho, “Gray and Color Image Contrast Enhancement by the Curvelet Transform”, IEEE Transactions On Image Processing, Vol. 12, NO. 6, 2003, Page(s):706-717.
[41] C.C. Sun, S. J. Ruan, M.-C Shie, and T.-W.Pai, ”Dynamic contrast enhancement based on histogram specification,” IEEE Trans. Consum. Electron., Vol. 51, no. 4, Page(s): 1300-1305, Nov. 2005
[42] J. Scott, M. Pusateri, “Towards Real-time Hardware Gamma Correction for Dynamic Contrast Enhancement”, Applied Imagery Pattern Recognition Workshop (AIPRW), 2009 IEEE, Page(s): 1-5
[43] Yihua Shi,” Adaptive Illumination Correction Considering Ordinal Characteristics”, Wireless Communications Networking and Mobile Computing (WiCOM), 2010 6th International Conference on, 2010, Page(s): 1-4
[44] Yihua Shi, Jinfeng Yang, Rembiao Wu, “Reducing illumination Based on Nonlinear Gamma Correction”, IEEE International Conference on Image Processing, 2007, Volume: 1, Page(s): 529-532
[45] J. A. Stark, “Adaptive image contrast enhancement usign generalizations of histogram equalization,” IEEE Trans. Image Process., vol. 9,no. 5, Page(s): 889–896, May 2000.
[46] Jianhong (Jackie) Shenand Yoon-Mo Jung (2006), Appl. Math. Optim., 53(3): 331-358, Weberized Mumford-Shah model with Bose-Einstein photon noise
[47] Jianhong (Jackie) Shen (2003), Physica D: Nonlinear Phenomena, 175(3/4): 241-251, On the foundations of vision modeling I. Weber’s law and WeberizedTV(total variation) restoration
[48] Li Tao and V. K. Asari, “Adaptive and integrated neighborhood-dependent approach for nonlinear enhancement of color images”, Journal of Electron Imaging, vol. 14, no. 4, Page(s): 043006-1-043006-14, Dec. 2005.
[49] A. Taguchi, T. Kimura, and M. Meguro., “Sharpening a noisy image by using fuzzy rules”, Nonlinear Image Processing IX, Page(s): 144-152, 1998
[50] S. C. Tai, Kang-Ming Li, "A sharpness enhancement algorithm with adaptive acutance compensation," Master's thesis, National Cheng Kung University, Tainan, Taiwan, R.O.C., 2009.
[51] S. C. Tai, Ting-Chou Tsai, "A Weight-Based Contrast Enhancement Algorithmby Clustered Histogram Equalization," Master's thesis, National Cheng Kung University, Tainan, Taiwan, R.O.C., 2011.
[52] C. Wang and Z. Ye, “Brightness preserving histogram equalization with maximum entropy: A variational perspective,” IEEE Trans. Consumer Electron., vol. 51, no. 4, Page(s):1326–1334, Nov. 2005.
[53] P. Whitele. Increments and decrements: Luminance discrimination. Vision Research, Page(s): 1677-1691, 1986